/*
 * Licensed to the Apache Software Foundation (ASF) under one
 * or more contributor license agreements.  See the NOTICE file
 * distributed with this work for additional information
 * regarding copyright ownership.  The ASF licenses this file
 * to you under the Apache License, Version 2.0 (the
 * "License"); you may not use this file except in compliance
 * with the License.  You may obtain a copy of the License at
 *
 *     http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing,
 * software distributed under the License is distributed on an
 * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
 * KIND, either express or implied.  See the License for the
 * specific language governing permissions and limitations
 * under the License.
 */

package org.apache.iotdb.db.mpp.aggregation.slidingwindow;

import org.apache.iotdb.db.mpp.aggregation.Accumulator;
import org.apache.iotdb.db.mpp.aggregation.Aggregator;
import org.apache.iotdb.db.mpp.plan.planner.plan.parameter.AggregationStep;
import org.apache.iotdb.db.mpp.plan.planner.plan.parameter.InputLocation;
import org.apache.iotdb.tsfile.exception.write.UnSupportedDataTypeException;
import org.apache.iotdb.tsfile.file.metadata.enums.TSDataType;
import org.apache.iotdb.tsfile.read.common.TimeRange;
import org.apache.iotdb.tsfile.read.common.block.TsBlock;
import org.apache.iotdb.tsfile.read.common.block.TsBlockBuilder;
import org.apache.iotdb.tsfile.read.common.block.column.Column;
import org.apache.iotdb.tsfile.read.common.block.column.ColumnBuilder;
import org.apache.iotdb.tsfile.read.common.block.column.TimeColumn;

import java.util.Arrays;
import java.util.Deque;
import java.util.LinkedList;
import java.util.List;
import java.util.stream.Collectors;

import static com.google.common.base.Preconditions.checkArgument;

public abstract class SlidingWindowAggregator extends Aggregator {

    // cached partial aggregation result of pre-aggregate windows
    protected Deque<PartialAggregationResult> deque;

    protected TimeRange curTimeRange;

    public SlidingWindowAggregator(
            Accumulator accumulator, List<InputLocation[]> inputLocationList, AggregationStep step) {
        super(accumulator, step, inputLocationList);
        this.deque = new LinkedList<>();
    }

    @Override
    public int processTsBlock(TsBlock tsBlock) {
        checkArgument(
                step.isInputPartial(),
                "Step in SlidingWindowAggregationOperator can only process partial result");
        TimeColumn timeColumn = tsBlock.getTimeColumn();
        Column[] valueColumn = new Column[inputLocationList.get(0).length];
        for (int i = 0; i < inputLocationList.get(0).length; i++) {
            InputLocation inputLocation = inputLocationList.get(0)[i];
            checkArgument(
                    inputLocation.getTsBlockIndex() == 0,
                    "SlidingWindowAggregationOperator can only process one tsBlock input.");
            valueColumn[i] = tsBlock.getColumn(inputLocation.getValueColumnIndex());
        }
        processPartialResult(new PartialAggregationResult(timeColumn, valueColumn));
        return 1;
    }

    @Override
    public void updateTimeRange(TimeRange curTimeRange) {
        this.curTimeRange = curTimeRange;
        evictingExpiredValue();
    }

    /**
     * evicting expired element in queue and reset expired aggregateResult
     */
    protected abstract void evictingExpiredValue();

    /**
     * update queue and aggregateResult
     */
    public abstract void processPartialResult(PartialAggregationResult partialResult);

    protected static class PartialAggregationResult {

        private final TimeColumn timeColumn;
        private final Column[] partialResultColumns;

        public PartialAggregationResult(TimeColumn timeColumn, Column[] partialResultColumns) {
            this.timeColumn = timeColumn;
            this.partialResultColumns = partialResultColumns;
        }

        public boolean isNull() {
            return partialResultColumns[0].isNull(0);
        }

        public long getTime() {
            return timeColumn.getLong(0);
        }

        public Column[] getPartialResult() {
            return partialResultColumns;
        }

        public List<TSDataType> getDataTypes() {
            return Arrays.stream(partialResultColumns)
                    .sequential()
                    .map(Column::getDataType)
                    .collect(Collectors.toList());
        }

        public Column[] opposite() {
            List<TSDataType> dataTypes = getDataTypes();
            TsBlockBuilder tsBlockBuilder = new TsBlockBuilder(dataTypes);
            ColumnBuilder[] columnBuilders = tsBlockBuilder.getValueColumnBuilders();
            Column[] results = new Column[partialResultColumns.length];
            for (int i = 0; i < partialResultColumns.length; i++) {
                switch (dataTypes.get(i)) {
                    case INT32:
                        columnBuilders[i].writeInt(partialResultColumns[i].getInt(0) * -1);
                        break;
                    case INT64:
                        columnBuilders[i].writeLong(partialResultColumns[i].getLong(0) * -1);
                        break;
                    case FLOAT:
                        columnBuilders[i].writeFloat(partialResultColumns[i].getFloat(0) * -1);
                        break;
                    case DOUBLE:
                        columnBuilders[i].writeDouble(partialResultColumns[i].getDouble(0) * -1);
                        break;
                    case TEXT:
                    case BOOLEAN:
                        throw new UnSupportedDataTypeException(
                                String.format("Unsupported data type in opposite : %s", dataTypes.get(i)));
                    default:
                        throw new IllegalArgumentException("Unknown data type: " + dataTypes.get(i));
                }
                results[i] = columnBuilders[i].build();
            }
            return results;
        }
    }
}
